Proposed Convolution Architecture for Monkeypox Detection using Dermoscopy Images

Monkeypox is a skin disease that spreadsfrom animals to people and then people to people, the class of the monkeypox is zoonotic and its genus are othopoxvirus. There is no special treatment for monkeypox but the monkeypox and smallpox symptoms are almost similar, so the antiviral drug developed for prevent from smallpox virus may be used for monkeypox Infected person, the Prevention of monkeypox is just like COVID-19 proper hand wash, Smallpox vaccine, keep away from infected person, used PPE kits. In this paper Deep learning is use for detection of monkeypox with the help of CNN model, The Original Images contains a total number of 228 images, 102 belongs to the Monkeypox class and the remaining 126 represents the normal. But in deep learning greater amount of data required, data augmentation is also applied on it after this the total number of images are 3192. A variety of optimizers have been used to find out the best result in this paper, a comparison is usedbased on Loss, Accuracy, AUC, F1 score, Validation loss, Validation accuracy, validation AUC, Validation F1 score of each optimizer. after comparing alloptimizer, the Adam optimizer gives the best result its total testing accuracy is 92.21%, total number of epochs used for testing is 100. With the help of deep learning model Doctors are easily detect the monkeypox virus with the single image of infected person. © 2023 IEEE.

Calculation of Electrostatic Potential Field of Coronavirus S Proteins for Brownian Dynamics Simulations

The Brownian dynamics method can give insight into the initial stages of the interaction of antiviral drug molecules with the structural components of bacteria or viruses. RAM of conventional personal computer allows calculation of Brownian dynamics of interaction of antiviral drugs with individual coronavirus S protein. However, scaling up this approach for modeling the interaction of antiviral drugs with the whole virion consisting of thousands of proteins and lipids is difficult due to high requirements for computing resources. In the case of the Brownian dynamics method, the main amount of RAM in the calculations is occupied by an array of values of the virion electrostatic potential field. When the system is increased from one S protein to the whole virion, the volume of data increases significantly. The standard protocol for calculating Brownian dynamics uses a three-dimensional grid with a spatial step of 1°A to calculate the electrostatic potential field. In this work, we consider the possibility of increasing the grid spacing parameter for calculating the electrostatic potential field of individual coronavirus S proteins. In this case, the amount of RAM occupied by the electrostatic potential field is reduced, which makes it possible to use personal computers for calculations. We performed Brownian dynamics simulations of interaction of an antiviral photosensitizer molecule with S proteins of three coronaviruses SARS-CoV, MERS-CoV, and SARS-CoV-2, and demonstrated that reduction of detalization of electrostatic potential field does not influence the results of Brownian dynamics much © The Authors 2022. This paper is published with open access at SuperFri.org

Drug Repositioning for Coronavirus (COVID-19) using Different Deep Learning Architectures

In December 2019, the COVID-19 epidemic was found in Wuhan, China, and soon hundreds of millions were infected. Therefore, several efforts were made to identify commercially available drugs to repurpose them against COVID-19. Inferring potential drug indications through computational drug repositioning is an efficient method. The drug repositioning problem is a top-K recommendation function that presents the most likely drugs for specific diseases based on drug and disease-related data. The accurate prediction of drug-target interactions (DTI) is very important for drug repositioning. Deep learning (DL) models were recently exploited for promising DTI prediction performance. To build deep learning models for DTI prediction, encoder-decoder architectures can be utilized. In this paper, a deep learning-based drug repositioning approach is proposed, which is composed of two experimental phases. Firstly, training and evaluating different deep learning encoder-decoder architecture models using the benchmark DAVIS Dataset. The trained deep learning models have been evaluated using two evaluation metrics;mean square error and the concordance index. Secondly, predicting antiviral drugs for Covid-19 using the trained deep learning models created during the first phase. In this phase, these models have been experimented to predict different antiviral drug lists, which then have been compared with a recently published antiviral drug list for Covid-19 using the concordance index metric. The overall experimental results of both phases showed that the most accurate three deep learning compound-encoder/protein-encoder architectures are Morgan/AAC, CNN/AAC, and CNN/CNN with best values for the mean square error, the first phase concordance index, and the second phase concordance index. © 2023,International Journal of Advanced Computer Science and Applications. All Rights Reserved.

Comparative Study of Molecular Docking, Structural, Electronic, and Fukui Function Studies on Favipiravir and its Newly Designed Derivatives (Potential Inhibitors) for COVID-19 Protease

Favipiravir is an antiviral medication currently being trialed as a COVID-19 treatment. These results motivate us to develop new species (possibly drugs) from favipiravir, perform comparative molecular docking, and reexamine their biological and pharmacological activities. Detailed quantum chemical research on favipiravir and its newly designed derivatives has been carried out with the help of DFT/B3LYP/6–311 + + G (d, p). In the present work, the structure of favipiravir has been modified and 12 new species have been modeled (all species are inherently stable because no virtual frequency is found during the vibration analysis). Reactivity of all species using various descriptors (local) such as Fukui function, local softness, electrophilicity, and global, i.e., electronegativity, hardness, HOMO–LUMO gap, etc. of the same are calculated and discussed. In silico studies such as molecular docking of all species and complete quantum chemistry studies suggest that four of them may mitigate the effects of the COVID-19 protease. © 2023 Wiley-VCH GmbH.

The SARS-CoV-2 Omicron Variant and its Multiple Sub-lineages: Transmissibility, Vaccine Development, Antiviral Drugs, Monoclonal Antibodies, and Strategies for Infection Control – a Review

The Omicron (B.1.1.529), fifth variant of concern (VOC) of SARS-CoV-2, initially identified following a steep increase in COVID-19 cases in Southern Africa in November 2021. It is a highly-mutated variant and is more contagious as compared with the Delta variant, however less deadly. Due to its high transmission rate, it spreads dramatically, and causing huge surges worldwide. It causes "mild infection”, with hospitalisations less likely to occur. However, this variant is known to show resistance to neutralizing antibodies (nAbs) generated through vaccination and/or prior infection as well as to monoclonal antibodies (mAbs) used to treat COVID-19 patients. In many countries, booster doses of vaccines have been recommended to increase the protective levels of antibodies in vaccinated individuals. Along with the implementation of appropriate prevention and control strategy measures, current efforts are also focussed on the development of better vaccines and mAbs to counter this variant. This review highlights the global health concerns and challenges posed by the Omicron variant and present an update on its sub-lineages. © 2023 Wiley-VCH GmbH.

SPATIAL GRAPH ATTENTION AND CURIOSITY-DRIVEN POLICY FOR ANTIVIRAL DRUG DISCOVERY

We developed Distilled Graph Attention Policy Network (DGAPN), a reinforcement learning model to generate novel graph-structured chemical representations that optimize user-defined objectives by efficiently navigating a physically constrained domain. The framework is examined on the task of generating molecules that are designed to bind, noncovalently, to functional sites of SARS-CoV-2 proteins. We present a spatial Graph Attention (sGAT) mechanism that leverages self-attention over both node and edge attributes as well as encoding the spatial structure - this capability is of considerable interest in synthetic biology and drug discovery. An attentional policy network is introduced to learn the decision rules for a dynamic, fragment-based chemical environment, and state-of-the-art policy gradient techniques are employed to train the network with stability. Exploration is driven by the stochasticity of the action space design and the innovation reward bonuses learned and proposed by random network distillation. In experiments, our framework achieved outstanding results compared to state-of-the-art algorithms, while reducing the complexity of paths to chemical synthesis. © 2022 ICLR 2022 - 10th International Conference on Learning Representationss. All rights reserved.

Non-neighbor Topological Indices on Covid-19 Drugs with QSPR Analysis

Coronavirus (COVID-19) is one of the recent infectious diseases caused by the virus SARS-CoV-2. The virus causes mild to severe respiratory problems which may lead to death in most cases. There is currently no precise or effective medication available to treat COVID-19 patients. Researchers and many pharmaceutical industries are working toward novel therapeutics and repurposed drugs for coronavirus. In this study, we consider some investigational antiviral drugs like Nitazoxanide, Imatinib, Famotidine, Galidesivir, and Artesunate that are used for the treatment of COVID-19. For this purpose, here we define various non-neighbor topological indices over the above aforesaid antiviral drugs to investigate the physicochemical properties associated with the indices. Further QSPR analysis was carried out between seven non-neighbor topological indices and eight physicochemical properties for the above drugs using the Linear regression method. The result obtained could aid in discovering new vaccines and drugs for COVID-19 disease. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

Coronavirus Disease 2019 (COVID-19): Current Situation and Therapeutic Options

Coronavirus disease 2019 (COVID-19) is defined as an illness caused by SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2). COVID-19 was first reported in the Wuhan, China, in late December, 2019. The World Health Organization (WHO) declared COVID-19 a global emergency on March 11, 2020. COVID-19 was rapidly transmitted and caused infection in 21,294,845 people and 761,779 deaths in more than 213 countries worldwide till August 16, 2020. United States of America (USA), Brazil, India, Russia Federation, Peru, Mexico, Colombia, Spain, France, Italy, Germany, and United Kingdom (UK) stand top COVID-19 affected countries in the world. The high transmission rate of COVID-19 might be due to large viral incubation time (2-14 days) and some modifications in the spike glycoprotein. Currently, effective drugs or vaccines are not developed for the treatment of novel coronavirus. However, few antibiotics like hydroxychloroquine and remdesivir have been currently used for the treatment of COVID-19 infection. Several collaboratives are working together for developing an effective and safe vaccine against COVID-19 and few vaccines are under clinical trial. Scientists are also working on plasma therapy and monoclonal antibodies. Nowadays, plasma therapy is considered the most effective treatment against COVID-19 and some promising results have been achieved. This review focuses on several therapeutic options for COVID-19, such as anti-viral drugs, vaccines, plasma therapy, and monoclonal antibodies. This review also covers the current situations of COVID-19 in the world. This review is about COVID-19, which will be beneficial to researchers for the development of potential treatment against it.Copyright © 2021 Bentham Science Publishers.

Vertex metric resolvability of COVID antiviral drug structures

In November of 2019 year, there was the first case of COVID-19 (Coronavirus) recorded, and up to 3rd of April of 2020, 1,116,643 confirmed positive cases, and around 59,158 dying were recorded. Novel antiviral structures of the 2019 pandemic disease Coronavirus are discussed in terms of the metric basis of their molecular graph. These structures are named arbidol, chloroquine, hydroxy-chloroquine, thalidomide, and theaflavin. Metric dimension or metric basis is a concept in which the whole vertex set of a structure is uniquely identified with a chosen subset named as resolving set. Moreover, the fault-tolerant concept of those structures is also included in this study. By this concept of vertex-metric resolvability of COVID antiviral drug structures are uniquely identified and help to study the structural properties of the structure. © 2023 - IOS Press. All rights reserved.

The First Electroanalytical Study Of Umifenovir (Arbidol) Used As A Potential Antiviral Drug For The Treatment of SARS-CoV-2: A Voltammetric Quantification On The Boron-Doped Diamond Electrode By Using Anionic Surfactant Media

In this work, an electroanalytical procedure for sensing umifenovir (arbidol) by square wave adsorptive stripping voltammetry (SW-AdSV) was developed utilizing an anodically pretreated boron-doped diamond electrode. Measurements of umifenovir using cyclic voltammetry with phosphate buffer solution (PBS, 0.1 M, pH 2.5) revealed irreversible behaviour, adsorption-controlled as well as an ill-defined (+1.13 V, PA1) and a well-defined (+1.47 V, PA2) two oxidation peaks. Umifenovir oxidations depend critically on supporting electrolytes and pH. The second oxidation peak (PA2) current of the umifenovir was enhanced by adding sodium dodecyl sulfate (SDS, anionic surfactant) in the chosen supporting electrolyte. Umifenovir was quantified using its second oxidation peak (PA2) at about +1.39 V. Using the optimized condition, the oxidation peak current of PA2 showed a linear relationship for umifenovir determination in the concentration range from 0.005 to 1.0 μg ml−1 (9.73 × 10−9−1.95 × 10−6 M), with a detection limit of 0.0014 μg ml−1 (2.72 × 10−9 M) in PBS (PH 2.5) with SDS. Finally, the developed approach was successfully utilized to determine umifenovir in the pharmaceutical formulation and urine samples. To the best of our knowledge, this is the first electroanalytical approach for voltammetric sensing of umifenovir. © 2023 The Electrochemical Society ("ECS”). Published on behalf of ECS by IOP Publishing Limited

Drug Repurposing for SARS-COV-2 Using Molecular Docking

Drug repurposing is an unconventional approach that is used to investigate new therapeutic aids of existing and shelved drugs. Recent advancement in technologies and the availability of the data of genomics, proteomics, transcriptomics, etc., and with the accessibility of large and reliable database resources, there are abundantly of opportunities to discover drugs by drug repurposing in an efficient manner. The recent pandemic of SARS-COV-2, that caused the death of 6,245,750 human beings to date, has tremendously increase the exceptional usage of bioinformatics tools in interpreting the molecular characterizations of viral infections. In this paper, we have employed various bioinformatics tools such as AutoDock-Vina, PyMol etc. We have found a leading drug candidate Cepharanthine (CEP) that has shown better results and effectiveness than recently used antiviral drug candidates such as Favipiravir, IDX184, Remedesivir, Ribavirin and etc. This paper has analyzed CEP's potential therapeutic importance as a drug of choice in managing COVID-19 cases. It is anticipated that proposed study would be beneficial for researchers and medical practitioners in handling SARS-CoV-2 and its variant related diseases. © 2022 IEEE.

Drug Repurposing for CoVID-19 Spike Protein through Molecular Docking

Drug repurposing is the technique of finding new uses for currently used or under-researched drugs. Because this strategy requires less time and money, it is thought to be a particularly effective drug development strategy. Due to current technological breakthroughs, the accessibility of vast and reliable database resources, as well as data accessibility from genomes, proteomics, transcriptomics, etc., there are numerous opportunities to identify drugs by drug repurposing. The recent SARS-COV-2 epidemic, which has so far claimed 6,245,750 lives, has significantly increased the use of bioinformatics techniques in deciphering the characteristics of viral diseases. Using FDA-approved antiviral drugs that target the COVID-19 spike protein, we have used a bioinformatics approach to drug repurposing to find possible effective inhibitors against the Coronavirus (COVID-19). We used a variety of bioinformatics tools in this study, including AutoDock-Vina, PyMol, and Discovery Studio, to identify a promising drug called Cepharanthine (CEP), which demonstrates successful outcomes and efficacy compared to recently used antiviral drug candidates like arbidol, talampicillin, bromhexine, chloroquine, lycorine, bruceine A, reserpine, indinavir, galidesiver, doxycycline, methisazone, flupentixol, trifluoperazine and fluoxetine. The potential therapeutic value of cepharanthine as a drug for treating COVID-19 has been investigated in this study. It is expected that the proposed study will help medical professionals and researchers cure disorders linked to Severe acute respiratory and variations of it. © 2022 IEEE.

RemCheck: A Novel Drug Validator Application to detect fake Remdesivir, an Anti-Viral Drug for COVID-19

The COVID-19 pandemic has turned out to be one of the dreadful disaster mankind has ever faced. With the subsequent waves of the pandemic setting in several countries, the number of cases being reported is quite alarming. People need to stay extremely vigilant and ensure strict adherence to social distancing, hand hygiene, and usage of personal protectives like masks, hand gloves and face shields. Remdesivir, an anti-viral drug used against the COVID-19, believed to have some therapeutic effects is on a surplus demand. There have been reports of illegal hoarding of these drugs. We need to be vigilant and keep a check on the circulation of fake Remdesivir drugs in the market amidst the pandemic. The study proposed development of a novel Drug Validator Application to detect fake Remdesivir drugs. This is done by scanning the carton or the vial of the Remdesivir drug through the dedicated Android application. This is further sent to the cloud server for processing. The AI model which runs in the cloud server evaluates the genuineness of the drug image. The report comprising the recommendation as Genuine or Fake is sent to the user through his/her registered mobile number and e-mail address. This application could curb the circulation of fake drugs in the market amidst the pandemic and could help in undertaking a real-time surveillance. © 2022 IEEE.

A Systematic Review on the Emergence of Omicron Variant and Recent Advancement in Therapies.

With the ongoing COVID-19 pandemic, the emergence of the novel Omicron variant in November 2021 has created chaos around the world. Despite mass vaccination, Omicron has spread rapidly, raising concerns around the globe. The Omicron variant has a vast array of mutations, as compared to another variant of concern, with a total of 50 mutations, 30 of which are present on its spike protein alone. These mutations have led to immune escape and more transmissibility compared to other variants, including the Delta variant. A cluster of mutations (H655Y, N679K, and P681H) present in the Omicron spike protein could aid in transmission. Currently, no virus-specific data are available to predict the efficacy of the anti-viral and mAbs drugs. However, two monoclonal antibody drugs, Sotrovimab and Evusheld, are authorized for emergency use in COVID-19 patients. This virus is not fading away soon. The easiest solution and least expensive measure to fight against this pandemic are to follow the appropriate COVID-19 protocols. There is a need to strengthen the level of research for the development of potential vaccines and anti-viral drugs. It is also important to monitor and expand the genomic surveillance to keep track of the emergence of new variants, thus avoiding the spread of new diseases worldwide. This article highlights the emergence of the new SARS-CoV-2 variant of concern, Omicron (B.1.1.529), and the vast number of mutations in its protein. In addition, recent advancements in drugs approved by FDA to treat COVID patients have been listed and focused in this paper.

IR Characterizations of Ribavirin, Chloroquine Diphosphate and Abidol Hydrochloride

Since the outbreak of novel coronavirus pneumonia (COVID-19), many research institutes and enterprises at home and abroad have been accelerating the research of COVID-19 (SARS-CoV-2) antibody drugs. However, the research on effective drugs was limited by the drug polymorphisms. The environment of drug production, storage and use also affected the stability of the drug. As a fast, non-destructive testing method, infrared spectroscopy can reflect the differences in drug structure, crystal form and even manufacturing technique to the vibration spectrum, which greatly improves the efficiency of R&D (research and development). In this paper, three clinical trials were considered effective drugs for the treatment of COVID-19: Chloroquine diphosphate, Ribavirin and Abidol hydrochloride. Their far-infrared spectrum (1~10 THz) and mid-infrared spectrum (400~4 000 cm-1) were measured by Fourier transform infrared spectrometer (FTIR). In the far-infrared spectrum, the characteristic peaks of Ribavirin were around 2.01, 2.68, 3.37, 4.05, 4.83, 5.45, 5.92, 6.42 and 7.14 THz;the characteristic peaks of Chloroquine phosphate were near 1.26, 1.87, 2.37, 3.06, 3.78, 5.09 and 6.06 THz;the characteristic peaks of Abidol hydrochloride were located near 2.24, 3.14, 3.72, 4.25 and 5.38 THz. Based on density functional theory, the B3LYP hybrid functional and 6-311++G (d, p) basis sets were selected to analyze the vibrational modes corresponding to all characteristic peaks in the spectrum using Crystal14 and Gaussian 16 software, and the accurate identification of the vibration spectrum was realized. The vibrational modes originated from the molecules' collective vibration in the far infrared region. In the mid-infrared band, below 2 800 cm-1, the vibrational modes mainly came from the in-plane and out-of-plane bending and rocking of the group;Above 2 800 cm-1, the vibrational modes transited to the in-plane stretching of C-H, O-H and N-H bonds. Taking the crystal structure with periodic boundary conditions as the initial configuration of the theoretical calculation would make the calculated spectrum more consistent with the experimental one, especially in the far-infrared band and the low-frequency band of mid-infrared (400~1 000 cm-1). This study was of great significance to deeply understand the pharmaceutical characteristics, drug interactions, control of drug production process, and guide the storage and use of antiviral drugs such as Chloroquine phosphate, Ribavirin and Abidol hydrochloride. © 2022 Science Press. All rights reserved.

A motley of possible therapies of the COVID-19: reminiscing the origin of the pandemic.

The 2019 outbreak of corona virus disease began from Wuhan (China), transforming into a leading pandemic, posing an immense threat to the global population. The WHO coined the term nCOVID-19 for the disease on 11th February, 2020 and the International Committee of Taxonomy of Viruses named it SARS-CoV-2, on account of its similarity with SARS-CoV-1 of 2003. The infection is associated with fever, cough, pneumonia, lung damage, and ARDS along with clinical implications of lung opacities. Brief understanding of the entry target of virus, i.e., ACE2 receptors has enabled numerous treatment options as discussed in this review. The manuscript provides a holistic picture of treatment options in COVID-19, such as non-specific anti-viral drugs, immunosuppressive agents, anti-inflammatory candidates, anti-HCV, nucleotide inhibitors, antibodies and anti-parasitic, RNA-dependent RNA polymerase inhibitors, anti-retroviral, vitamins and hormones, JAK inhibitors, and blood plasma therapy. The text targets to enlist the investigations conducted on all the above categories of drugs, with respect to the COVID-19 pandemic, to accelerate their significance in hindering the disease progression. The data collected primarily targets recently published articles and most recent records of clinical trials, focusing on the last 10-year database. The current review provides a comprehensive view on the critical need of finding a suitable treatment for the currently prevalent COVID-19 disease, and an opportunity for the researchers to investigate the varying possibilities to find and optimized treatment approach to mitigate and ameliorate the chaos created by the pandemic worldwide.

Complementing RNA Detection with Pharmaceutical Monitoring for Early Warning of Viral Outbreaks through Wastewater-Based Epidemiology

Wastewater-based epidemiology using viral nucleic acids to predict community viral outbreaks has many challenges, including differences in viral shedding of infected individuals and interference from the wastewater matrix. In this study, we demonstrate that monitoring pharmaceutical residues in untreated sewage provides complementary information that correlates with future occurrences of viral outbreaks. We monitored 63 pharmaceutically active compounds, including antivirals used to treat COVID-19 and influenza and over-the-counter drugs commonly used to relieve the symptoms of infection. Weekly sampling was conducted at four municipal sewage treatment plants in Western New York. Residues of drugs associated with managing COVID-19 symptoms were detected, including azithromycin (1.99-5.00 μg/L), chloroquine (0.01-33.00 μg/L), hydroxychloroquine (0.05-30.54 μg/L), and lopinavir (13.75-181.20 μg/L). A significant correlation (p < 0.001) was observed between the total COVID-19-related drugs detected and the 5-day rolling averages of reported cases. Acetaminophen concentrations spiked approximately 2.5 weeks before a spike in SARS-CoV-2 RNA copies in all wastewater treatment plants sampled. The results suggest over-the-counter analgesic concentrations, in particular, acetaminophen in raw sewage to be used to complement viral RNA data as an early warning system for effective management of viral outbreaks at the community level. © 2022 American Chemical Society.

Progress on COVID-19 chemotherapeutics

COVID-19 has caused the outbreak to spread on a global scale due to its high transmission rate and ineffective prevention and treatment. The disease is caused by a new type of single-stranded RNA coronavirus, which was named SARS-CoV-2 by the International Committee on Taxonomy of Viruses. As of November 2021, more than 210 countries and regions around the world have been affected by the coronavirus, and a total of more than 240 million confirmed cases have been reported worldwide, and the death toll has exceeded 4 million. Although the vaccine immunizations have alleviated the COVID-19 pandemic to some extent, however from the perspective of clinical treatment, the development of effective antiviral therapeutics for COVID-19 remains urgent and long-term need. Remdesivir (Veklury, Gilead), which was approved by the US FDA in October 2020, is currently the only officially approved coronavirus polymerase inhibitor. However, the clinical efficacy of remdesivir for COVID-19 remains contentious, as the statistical differences in both mortality rate and clinical improvement between drug-treated and control groups were not clearly verified in several trials. Very recently following remdesivir, Merck announced the first effective antiviral pill against COVID-19 called molnupiravir, which has finished phase III clinical trials with proven efficacy to reduce the risk of hospitalizations and deaths by 50% in patients with mild-to-moderate COVID-19. Based on this result, Merck received the first authorization from the UK (as of November 9, 2021). It is also known that one more antiviral pill developed by Pfizer with the compound code PF-07321332, is already in the final stages of trial data analysis, so it is expected that this will be the second orally available drug for authorization application in the coming few months. Despite the encouraging results achieved by Merck and Pfizer's scientists, the practical challenges and high attrition rates on new drug development remain a difficult reality for the medicinal chemists and pharmaceutical scientists. In this article, we provide an overview of the research hotspots of the development for COVID-19 treatment agents, especially on the representative antiviral compounds that have potential inhibitory effects against SARS-CoV-2. By focusing on specific biotargets of SARS-CoV-2 and their drug molecules, mechanism strategies, and their clinical testing results, we summarize the opportunities and challenges faced by drug developers in stopping the COVID-19 pandemic. This review further provides the current status on development of COVID-19 chemotherapeutics and outlines some future perspectives on potential innovation strategies to mitigate the risk in the new drug discovery. © 2022, Science Press. All right reserved.

The pill of recovery; Molnupiravir for treatment of COVID-19 patients; a systematic review.

Background: Throughout the time of the global pandemic of SARS-CoV-2 virus, there has been a compelling necessity for the development of effective antiviral agents and prophylactic vaccines to limit the virus spread, disease burden, hospitalization, and mortality. Until mid of 2021, the NIH treatment guideline declared no single oral therapy was proven to treat mild to moderate cases. A new hope arose when a repurposed direct acting oral anti-viral agent "Molnupiravir" was shown to be effective in decreasing mortality and need for hospitalization in mild to moderate cases with relatively good safety profile; exhibiting a significant reduction in virus titers only after two days from administration. Molnupiravir recently granted the FDA emergency use authorization to treat mild to moderate COVID-19 patients with at least one risk factor for progression. Methods: We performed a computer-based literature search of (PubMed, Science direct, MedRxiv, BioRxiv, ClinicalTrials.gov, ISRCTN, Cochrane COVID study register, EU registry, and CTRI registry) till February 15th, 2022. The following keywords were used in our search ("Molnupiravir", "NHC", "EIDD-2807", "MK-4482" or "EIDD-1931"). Results: We identified from the initial search a total of 279 articles; 246 articles (BioRxiv and MedRxiv N = 186, PubMed N = 33, Science direct N = 27) and 33 Clinical trials from the following registries (ISCTRN (N = 1), Clinical Trials.gov (N = 6), CTRI (N = 12), Cochrane (N = 14)). Through screening phases, 21 records were removed as duplicates and 198 irrelevant records were also excluded. The included studies in this systematic review were (N = 60) included 39 published papers and 21 clinical trials. After Manual addition (N = 4), the qualitative assessment included (N = 64). Conclusion: Based on the cumulative evidence from preclinical and clinical studies, Molnupiravir is proven to be a well tolerated, direct acting oral anti-viral agent to halt the disease progression in mild to moderate COVID-19 cases; in terms of mortality and hospitalization rates.

Transmission of COVID-19 From an Asymptomatic Mother to Fetus Leading to Death of Neonate From Pneumonia.

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) responsible for the coronavirus disease 2019 (COVID-19) pandemic has rarely impacted neonates. When infection does occur, it is typically asymptomatic. We describe a case of a neonate born to a 25-year-old mother who was COVID-19 positive but asymptomatic. An emergent cesarean section was performed during week 30 of gestation due to category three fetal heart tracings. The neonate, unfortunately, died on the day of life 12 from respiratory distress secondary to severe COVID-19 pneumonia. This is an important case that illustrates the deleterious impact COVID-19 infection can have on neonates. It is a unique case of the compassionate use of remdesivir for a neonate. The patient's respiratory decline soon after birth, lends support that the virus responsible for COVID-19 can be transmitted vertically.